AIMC Topic: Brain

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Functional connectome-based predictive modeling of suicidal ideation.

Journal of affective disorders
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy.

EBioMedicine
BACKGROUND: Valid non-invasive biomarkers for Parkinson's disease (PD) and Parkinson-plus syndrome (PPS) are urgently needed. Based on our recent self-supervised vision foundation model the Shift Window UNET TRansformer (Swin UNETR), which uses clini...

Advances in brain-targeted delivery strategies and natural product-mediated enhancement of blood-brain barrier permeability.

Journal of nanobiotechnology
The blood-brain barrier (BBB) represents a formidable challenge in the treatment of neurological disorders, as it restricts the passage of most therapeutic agents into the central nervous system (CNS). Research in brain-targeted delivery strategies a...

Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.

BMC psychiatry
BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abno...

Sex-related differences and associated transcriptional signatures in the brain ventricular system and cerebrospinal fluid development in full-term neonates.

Biology of sex differences
BACKGROUND: The cerebrospinal fluid (CSF) is known to serve as a unique environment for neurodevelopment, with specific proteins secreted by epithelial cells of the choroid plexus (CP) playing crucial roles in cortical development and cell differenti...

A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights.

Journal of neuroengineering and rehabilitation
BACKGROUND: Major Depressive Disorder is a leading cause of disability worldwide. An accurate assessment of depression severity is critical for diagnosis, treatment planning, and monitoring, yet current clinical tools are largely subjective, relying ...

SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection.

Scientific data
Hyperspectral imaging (HSI) and machine learning (ML) have been employed in the medical field for classifying highly infiltrative brain tumours. Although existing HSI databases of in vivo human brains are available, they present two main deficiencies...

Resting-State Functional MRI Reveals Altered Seed-Based Connectivity in Diabetic Osteoporosis Patients.

Clinical interventions in aging
BACKGROUND: Diabetic osteoporosis (DOP) can cause abnormal brain neural activity, but its mechanism is still unclear. This study aims to further explore the abnormal functional connectivity between different brain regions based on the team's previous...

Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods.

Sensors (Basel, Switzerland)
Driven by the remarkable capabilities of machine learning, brain-computer interfaces (BCIs) are carving out an ever-expanding range of applications across a multitude of diverse fields. Notably, electroencephalogram (EEG) signals have risen to promin...